[BioC] Positive correlation between dye-swap technical replicates

[Juan Pedro Steibel]

Hello Michal,
Before anything...
Have you checked your raw data? When we have dye swaps and a reference 
design we usually do pairwise plots... then check the sign of the slope 
or correlation coefficient with the expected value. opposite sign points 
at mislabeling or other technical errors. This should be obvious even 
before ANY pre-processing.

I will let the limma gurues to tackle the corresponding questions.
cheers!
JP



Micha? Góralski wrote:
> Dear All,
>
> I have some doubts concerning linear model used in my data analysis. I 
> was searching for the answer on the mail list but I didn't find the 
> similar case.
> I analyse tobacco roots treated with 2 types of stress: NaCl and 
> CdCl2. I have pooled common reference and I have 3 biological 
> replicates of treated plants. I also did dye swaps as technical 
> replicate.
> This is my targets file:
> SlideNumber Name FileName Cy3 Cy5
> 13244317 21 13244317.gpr Control NaCl
> 13244318 22 13244318.gpr Control NaCl
> 13244315 23 13244315.gpr Control NaCl
> 13244319 31 13244319.gpr Control CdCl2
> 13244337 32 13244337.gpr Control CdCl2
> 13244316 33 13244316.gpr Control CdCl2
> 13244330 21 13244330.gpr NaCl Control
> 13244329 22 13244329.gpr NaCl Control
> 13244331 23 13244331.gpr NaCl Control
> 13244333 31 13244333.gpr CdCl2 Control
> 13244335 32 13244335.gpr CdCl2 Control
> 13244336 33 13244336.gpr CdCl2 Control
>
> I did background subtraction with method "normexp" and normalization 
> "pronttip loess", without normalization between arrays.
>
> Now I have the vector indicating biological and technical replicates.
>
> >biolrep=c(1,2,3,4,5,6,1,2,3,4,5,6)
>
> and create model matrix:
>
> >design=modelMatrix(targets, ref="Control")
> > design
> CdCl2 NaCl
> [1,] 0 1
> [2,] 0 1
> [3,] 0 1
> [4,] 1 0
> [5,] 1 0
> [6,] 1 0
> [7,] 0 -1
> [8,] 0 -1
> [9,] 0 -1
> [10,] -1 0
> [11,] -1 0
> [12,] -1 0
>
> I'm interested in such contrasts:
>
> >cmatrix=makeContrasts(NaCl, CdCl2, NaCl-CdCl2,levels=design)
> > cmatrix
> Contrasts
> Levels NaCl CdCl2 NaCl - CdCl2
> CdCl2 0 1 -1
> NaCl 1 0 1
>
> Object for duplicate correlation with dye-swaps:
>
> >corfit=duplicateCorrelation(MA, design=design, ndups=1, block=biolrep)
>
> and the first problem is:
> > corfit$consensus
> [1] 0.3926545
>
> In limma manual it is written that correlation should be negative for 
> dye swaps- why is it positive?- is it a question of wrong model matrix 
> or is it something wrong with my samples?
>
> but
>
> When I do simple hierarchical clustering of log-ratios:
> >dist.matrix=dist(t(MA$M))
> >hc=hclust(dist.matrix)
> >par(mfrow=c(1,1)
> >plot(hc)
>
> The plot divides my arrays in two groups that exactly reflects dye 
> swaps. So maybe the model is correct?
>
> I was thinking also about checking dye effect so I tried with such model:
>
> > design2=cbind(Dye=1, design)
> > design2
> Dye CdCl2 NaCl
> [1,] 1 0 1
> [2,] 1 0 1
> [3,] 1 0 1
> [4,] 1 1 0
> [5,] 1 1 0
> [6,] 1 1 0
> [7,] 1 0 -1
> [8,] 1 0 -1
> [9,] 1 0 -1
> [10,] 1 -1 0
> [11,] 1 -1 0
> [12,] 1 -1 0
>
> I'm not sure if I can use such model.
> if I use it:
>
> > corfit=duplicateCorrelation(MA, design=design2, ndups=1, 
> block=blockrep)
> > corfit$consensus
> [1] -0.04530506
>
> The second problem is that each probe on my array is duplicated so in 
> the final top table I have each gene doubled- I read it is not 
> possible in Limma to analyse both technical duplicates and gene 
> replicas on the array. Could you give me any hint how to solve this 
> problem?
>
> I will be glad for any help in this cases
>
> Best regards,
>
> Michal Goralski, PhD student,
> Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, 
> Poland.
>
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>


-- 
=============================
Juan Pedro Steibel

Assistant Professor
Statistical Genetics and Genomics

Department of Animal Science & 
Department of Fisheries and Wildlife

Michigan State University
1205-I Anthony Hall
East Lansing, MI
48824 USA 

Phone: 1-517-353-5102
E-mail: steibelj at msu.edu